Tag: PYMC3

Got `AttributeError` from `from_pymc3` of ArviZ

You are passing return_inferancedata=True to pm.sample(), which according to the PyMC3 documentation will return an InferenceData object rather than a MultiTrace object. return_inferencedatabool, default=False Whether to return the trace as an arviz.InferenceData (True) object or a MultiTrace (False) Defaults to False, but we’ll switch to True in an upcoming release….

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Bayesian Open Source Software for Biomedicine: Stan, ArviZ and PyMC3

Back to Proposal List Projects PyMC, ArviZ, Stan Lead Christopher Fonnesbeck (NumFOCUS) Funding Cycle 4 Proposal Summary To develop key infrastructure updates and collaboration resources for state-of-the-art Bayesian modeling software libraries. Project PyMC PyMC3 is the current version of the PyMC open source probabilistic programming framework for Python, having been…

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python xarray – PyMC3/Arviz: CDF value from trace

I have a sample from PyMC3 and I’m trying to get a cumulative probability from it, e.g. P(X < 0). I currently use this: trace = pymc3.sample(return_inferencedata=True) prob_x_lt_zero = (trace.posterior.X < 0).sum() / trace.posterior.X.size Is there a better way to do this, either with some helper function from Arviz or…

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PyMC3: Different predictions for identical inputs

I don’t think it’s a bug and I also don’t find it troubling. Since PyMC3 doesn’t check whether the points being predicted are identical, it treats them separately and each one results in a random draw from the model. While each PPC draw (row in ppc[‘y’]) is using the same…

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Installation issues with PyMC3 – Stackify

Just had this problem and found a solution. When searching (with Bing or Google) for conda install of pymc3, several links come up. The first is with conda-forge: conda install -c conda-forge pymc3 DO NOT USE THIS or you will get the error messages in the above posts. I have…

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Stan vs PyMC3 vs Bean Machine

I have been a light user of Stan and RStan for some time and while there are a lot of things I really like about the language (such as the awesome community you can turn to for support and ShinyStan for inspecting Stan output) there are also a few things…

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Classification Problem using Pymc3 – Questions

Hello everyone!I am trying to figure out how to do a classification task using the pymc3 library. I have read an amazing article on how to achieve that but the article caters to the classification problem having only two features (target variable included). In the article, the author samples one…

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How would I take this prior distribution and evidence and plug it into pymc3? – Questions

Hi, I’m familiar with Bayesian updates using discrete data – but I’m confused on how to do the same thing for continuous data, and someone recommended PyMC3. Here’s my example: My somewhat informative prior distribution of outcomes is this: import numpy as np import matplotlib.pyplot as plt from scipy.stats import…

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Recovering Bimodal distribution parameters using pymc3

{“container_id”:”1d9e5ad015e2e03cef94e691be4438b53a70630ff139319b924402f64bf7f381″,”severity”:”INFO”,”time”:”2021/12/23 16:28:39.257154″,”line”:”java_template.go:63″,”message”:”Using launch args: [-cp /template/datastream-to-spanner/*:/template/datastream-to-spanner/libs/*:/template/datastream-to-spanner/classes com.google.cloud.teleport.v2.templates.DataStreamToSpanner –tempLocation=gs://dataflow-staging-us-central1-664290125703/tmp –labels={n “goog-dataflow-provided-template-name” : “cloud_datastream_to_spanner”,n “goog-dataflow-provided-template-type” : “flex”n}n [email protected]com –streamName=ora2span1 –databaseId=quiz-database –inputFilePattern=gs://shailesh-ds1/data1/ –runner=DataflowRunner –project=shailesh-1 –jobName=daedwedfwedfeadfsedfesd –templateLocation=gs://dataflow-staging-us-central1-664290125703/staging/template_launches/2021-12-23_08_27_41-9888970193837049959/job_object –stagingLocation=gs://dataflow-staging-us-central1-664290125703/staging –region=us-central1 –instanceId=quiz-instance]”} {“container_id”:”1d9e5ad015e2e03cef94e691be4438b53a70630ff139319b924402f64bf7f381″,”severity”:”INFO”,”time”:”2021/12/23 16:28:39.257196″,”line”:”exec.go:38″,”message”:”Executing: java -cp /template/datastream-to-spanner/*:/template/datastream-to-spanner/libs/*:/template/datastream-to-spanner/classes com.google.cloud.teleport.v2.templates.DataStreamToSpanner –tempLocation=gs://dataflow-staging-us-central1-664290125703/tmp –labels={n “goog-dataflow-provided-template-name” : “cloud_datastream_to_spanner”,n “goog-dataflow-provided-template-type” : “flex”n}n [email protected]com –streamName=ora2span1 –databaseId=quiz-database –inputFilePattern=gs://shailesh-ds1/data1/ –runner=DataflowRunner –project=shailesh-1 –jobName=daedwedfwedfeadfsedfesd –templateLocation=gs://dataflow-staging-us-central1-664290125703/staging/template_launches/2021-12-23_08_27_41-9888970193837049959/job_object –stagingLocation=gs://dataflow-staging-us-central1-664290125703/staging –region=us-central1…

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python – How to implement Bayesian Inference correctly with pymc3?

I have been working with pymc3 for a while and I was observing the several tutorials with examples. However, I am not sure if I am approaching the Bayesian InFerence method correctly. Find below my approach: from pymc3.distributions import Interpolated import numpy as np # import warnings # import sys…

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python – How to get the Cumulative Distribution Function with PyMC3?

I am trying to recreate the models in John Kruschke’s ‘Doing Bayesian Data Analysis‘ and am currently trying to model ordinal data (chapter 23 in the book. This is the JAGS model that I’m trying to recreate: total = length(y) #Threshold 1 and nYlevels-1 are fixed; other thresholds are estimated….

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[pymc-devs/pymc] pymc3 does not work properly with lower versions of Glibc

Description of your problem I am trying to install pymc3 on a centos6 server. The various environment software versions on the server are relatively low. I used miniconda3 to create an environment to install pymc3, and I can install it successfully, but it reports an error when importing pymc3. Please…

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Very slow sampling. Still can’t find what is happening after checking FAQs – Questions

I was using Pycharm with Python 3.7.4 and I was trying to learn from this tutorial:docs.pymc.io/en/v3/pymc-examples/examples/generalized_linear_models/GLM.html After pip install pymc3, I imported it and with 3 warnings:import pymc3WARNING (theano.configdefaults): g++ not available, if using conda: conda install m2w64-toolchainWARNING (theano.configdefaults): g++ not detected ! Theano will be unable to execute optimized…

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Sp.stats and PyMC3 logps different – Questions

Hi everyone, I am fitting a geometric distribution to the following data: [40000, 600, 1500, 30000, 12000, 25000, 65000, 1500, 40000, 10000000, 25000, 2000, 2000, 500, 800, 1500, 30000, 850, 25000, 1000, 15000, 40000, 9000, 3000, 12000, 1000, 1000, 1500, 10000, 25000, 7000, 35000, 30000, 25000, 750, 20000, 7000, 1500,…

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